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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 2
621-625,629

Multi-scale balanced deep hashing method for image retrieval

Zhang Yichao1
Huang Zhangcan1
Chen Yaxiong2,3
1. Dept. of Mathematics, School of Science, Wuhan University of Technology, Wuhan 430070, China
2. Xi'an Institute of Optics & Precision Mechanics, Chinese Academy of Sciences, Xi'an 710048, China
3. University of Chinese Academy of Sciences, Beijing 100049, China
DOI: 10.19734/j.issn.1001-3695.2017.10.0962

Abstract

The use of the semantic similarity improving the hash coding quality has recently been more widely concerned. Traditional supervised hash methods for image retrieval represent an image as a manual feature vector or a machine learning feature vector, and then perform a separate quantization step to generate a binary code. Such methods do not control the quantization error effectively, and cannot guarantee the balance of hash code. To this end, this paper presented a new multi-scale balanced deep hash method. The method used multi-scale input, which effectively improved the ability of learning the image features from the network. Moreover, it proposed a new loss function. Under the premise of preserving the semantic similarity, it took the quantization error and the balance of hash code into account to generate the high quality hash code. After experimenting on two benchmark databases: CIFAR-10 and Flickr, this method has been improved by 5.5% and 3.1% of the search accuracy compared with today's advanced image retrieval methods.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.10.0962
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 2
Section: Technology of Graphic & Image
Pages: 621-625,629
Serial Number: 1001-3695(2019)02-066-0621-05

Publish History

[2019-02-05] Printed Article

Cite This Article

张艺超, 黄樟灿, 陈亚雄. 一种多尺度平衡深度哈希图像检索方法 [J]. 计算机应用研究, 2019, 36 (2): 621-625,629. (Zhang Yichao, Huang Zhangcan, Chen Yaxiong. Multi-scale balanced deep hashing method for image retrieval [J]. Application Research of Computers, 2019, 36 (2): 621-625,629. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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